Severe Pandemic Planning Assumptions May Be Too Low

By Eric Toner, M.D., June 2, 2006

California recently proposed an ambitious $400 million plan for pandemic preparedness that includes $347 million to prepare hospitals and increase surge capacity [1]. The California planners predict that a pandemic of only moderate severity would require many more critical care beds and ventilators than what HHS predicted for a severe pandemic in its Pandemic Influenza Plan (11/2005, p. 16). This difference is the product of the assumptions on which each plan’s calculations were based, and the planning implications of those differences are significant. The California plan addresses a much bigger outbreak than that predicted by the HHS numbers, and the results underscore the critical importance of using the most reasonable planning assumptions possible.

The CDC’s FluSurge 2.0 software projects the effect of a pandemic on hospitals, based on factors such as attack rate, duration of outbreak, and hospitalization rates. The default FluSurge assumptions are based on the experience of the 1968 pandemic, which was the mildest pandemic on record. With some alterations, FluSurge can be used to predict the effects of other pandemic scenarios, but that raises an important question – which assumptions are best?

In its Pandemic Influenza Plan, HHS applied the FluSurge 1968-like assumptions to a severe pandemic, adjusting only the hospitalization rate. The result is a projected need for many more hospital beds, ICU beds and ventilators than exist in the country. While these numbers are bad, they may actually be much too low if the other assumptions are off.

The California planners used FluSurge as well but made major changes to that program’s default numbers. The table below compares the California, CDC, and HHS planning assumptions:

California

CDC:1968-like*

HHS:1918-like

Hospitalization rate for infected people

4.4%

0.1%

11%

Inpatient mortality rate

27%

17.7%

13%

% of inpatients needing ICU care

35%

15%

15%

% of inpatients needing ventilators

30%

7.5%

7.5%

*FluSurge default

The California planners first adjusted the age distribution of illness and death. FluSurge uses a distribution of age-related morbidity and mortality in which almost all hospitalization and deaths occur among those aged 65 and above, a group that comprises only 12% of the population. However, in 1918, there was much greater morbidity and mortality among the much larger cohort of young adults, aged 20 to 64. Therefore, California planners averaged the 1968 and 1918 age-specific risk for each age group, which resulted in a higher percentage of hospitalization and death. A much higher inpatient mortality rate makes sense if it is assumed that hospital beds will be a scarce commodity and that only very sick patients will be admitted.

The California plan also assumes a much higher utilization rate for critical care and mechanical ventilation, based on the argument that the number of inpatients needing ventilators and critical care must be higher than the number who die in the hospitals since almost all patients who would die of flu would also be candidates for critical care before their death. By this logic, the CDC/HHS assumption for the percentage of patients needing ventilators is particularly low.

Consequently, California predicts that on week 5 of an 8 week moderate outbreak, with a 25% attack rate, flu patients would utilize 400% of hospital beds, 1200% of ICU beds, and 470% of ventilators. The numbers would be much worse if the assumptions were based on a severe 1918-like scenario.

If one accepts this approach, then the calculations currently being used by HHS for a severe pandemic are too low by several orders of magnitude.

Clearly, different assumptions produce very different results. The authors of the California plan convincingly argue that it is inappropriate to use1968-like numbers to model a 1918-like pandemic. Whether the California group has chosen the right numbers is difficult to determine, and it is counterproductive to use numbers that are much too large. Therefore, given that the assumptions used in modeling make such a big difference in results, and those results drive planning and budgeting, it is vitally important that the best possible assumptions are used, which means they should represent a consensus of the country’s most experienced experts.

The CDC and HHS should review their planning assumptions and incorporate input from outside experts in clinical medicine and hospital disaster planning. Until this happens, hospital, state and local planners should use FluSurge for modeling and planning only after determining the most appropriate numbers to input into the program for modeling, predicting, and planning for the effects of a flu pandemic.